…tem (deepmodeling#4876)

# Fix: support "max:N" and "filter:N" batch_size rules in
DeepmdDataSystem

## Problem

- Using `batch_size: "max:..."` or `"filter:..."` in configs caused:
- `RuntimeError: unknown batch_size rule max` during the PyTorch path
(neighbor statistics).
- Docs mention these rules and PyTorch `DpLoaderSet` already supports
them, so behavior was inconsistent across layers.

## Cause

- The common data layer `DeepmdDataSystem` only implemented `"auto"` and
`"mixed"` for string `batch_size`, missing `"max"` and `"filter"`.
- PT training performs neighbor statistics via `DeepmdDataSystem` before
real training, so it failed early when those rules were used.

## Fix

- Implement `"max:N"` and `"filter:N"` in `DeepmdDataSystem.__init__` to
mirror `DpLoaderSet` semantics:
- `max:N`: per-system `batch_size = max(1, N // natoms)` so `batch_size
* natoms <= N`.
- `filter:N`: drop systems with `natoms > N` (warn if any removed; error
if none left), then set per-system `batch_size` as in `max:N`.
- After filtering, update `self.data_systems`, `self.system_dirs`, and
`self.nsystems` before computing other metadata.

## Impact

- Aligns the common layer behavior with PyTorch `DpLoaderSet` and with
the documentation.
- Prevents PT neighbor-stat crashes with configs using
`"max"`/`"filter"`.

## Compatibility

- No change to numeric `batch_size` or existing
`"auto"/"auto:N"/"mixed:N"` rules.
- TF/PT/PD paths now accept the same `batch_size` rules consistently in
the common layer.

## Files Changed

- `deepmd/utils/data_system.py`: add parsing branches for `"max:N"` and
`"filter:N"` in `DeepmdDataSystem.__init__`.

```python
elif "max" == words[0]:
                # Determine batch size so that batch_size * natoms <= rule, at least 1
                if len(words) != 2:
                    raise RuntimeError("batch size must be specified for max systems")
                rule = int(words[1])
                bs = []
                for ii in self.data_systems:
                    ni = ii.get_natoms()
                    bsi = rule // ni
                    if bsi == 0:
                        bsi = 1
                    bs.append(bsi)
                self.batch_size = bs
            elif "filter" == words[0]:
                # Remove systems with natoms > rule, then set batch size like "max:rule"
                if len(words) != 2:
                    raise RuntimeError("batch size must be specified for filter systems")
                rule = int(words[1])
                filtered_data_systems = []
                filtered_system_dirs = []
                for sys_dir, data_sys in zip(self.system_dirs, self.data_systems):
                    if data_sys.get_natoms() <= rule:
                        filtered_data_systems.append(data_sys)
                        filtered_system_dirs.append(sys_dir)
                if len(filtered_data_systems) == 0:
                    raise RuntimeError(f"No system left after removing systems with more than {rule} atoms")
                if len(filtered_data_systems) != len(self.data_systems):
                    warnings.warn(f"Remove {len(self.data_systems) - len(filtered_data_systems)} systems with more than {rule} atoms")
                self.data_systems = filtered_data_systems
                self.system_dirs = filtered_system_dirs
                self.nsystems = len(self.data_systems)
                bs = []
                for ii in self.data_systems:
                    ni = ii.get_natoms()
                    bsi = rule // ni
                    if bsi == 0:
                        bsi = 1
                    bs.append(bsi)
                self.batch_size = bs
```

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **New Features**
* Added support for "max" and "filter" batch size rules, allowing more
flexible control over batch sizing and filtering of data systems based
on atom counts.
* **Bug Fixes**
* Improved error handling for incorrect batch size string formats and
cases where no systems remain after filtering.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>